code: def extract_test_info(
      test_results: model_handler.TestResultCollection,
  ) -> DataFrame:
      """Extracts the test information."""
      column_names = list(
          itertools.chain(
              model_handler.ModelConfig._fields,
              ["enable_gpu", "trt_model"],
              trt.TrtConversionParams._fields,
          )
      )
      rows = []
      for result in test_results.results:
          r = list(result.model_config) + [result.enable_gpu]
          if result.trt_convert_params is not None:
              r += [True] + list(result.trt_convert_params)
          else:
              r += [False] + [
                  None for _ in trt.TrtConversionParams._fields
              ]
          rows.append(r)
      return DataFrame(column_names=column_names, rows=rows)
  
imports: import itertools
  import json
  from typing import Any, Callable, Optional, Sequence, Tuple, Union
  from collections import namedtuple
  import numpy
  from tensorflow.python.compiler.tensorrt.model_tests import model_handler
  import tensorflow.python.compiler.tensorrt.trt_convert
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 1 for calling a global function with example usage: extract_test_info(test_results) and returns: DataFrame